DD1418 Language Engineering with Introduction to Machine Learning
KTH Royal Institute of Technology
- Knowledge and skills in programming, 6 higher education credits, equivalent to completed course DD1310/DD1311/DD1312/DD1314/DD1315/DD1316/DD1318/DD1331/DD1337/DD100N/ID1018.
- Knowledge in basic computer science, 6 higher education credits, equivalent to completed course DD1320/DD1321/DD1325/DD1327/DD1338/ID1020/ID1021.
- Knowledge in probability theory, 6 higher education credits, equivalent to completed course SF1912/SF1914-SF1924.
Active participation in a course offering where the final examination is not yet reported in LADOK is considered equivalent to completion of the course. Registering for a course is counted as active participation. The term 'final examination' encompasses both the regular examination and the first re-examination.
Theory:
The historical development and bases of language engineering, morphology, syntax, semantics, vector space models, evaluation methods, machine learning, information theory and Markov models.
Methods::
Morphological analysis, generation and language statistics and corpus processing, parsing, generation, part-of-speech tagging, named entity recognition, probabilistic parsing and statistical lexical semantics.
Application areas:
Spelling and grammar checking, information retrieval, word prediction for smart text entry, text clustering and text categorization, computer-aided language learning, dialogue systems, speech technology and machine translation.
After passing the course, the student shall be able to
- explain and use basic concepts in linguistics, language engineering and machine learning
- apply language engineering concepts, methods and tools to build language engineering systems as well as be able to explain the structure of such systems
- implement standard methods in language engineering
- design and carry out simple evaluations of a language engineering system as well as interpret the results,
- independently be able to solve a well delimited practical language engineering problem
in order to be able to
- work with a bachelor's degree project with a focus on language engineering or machine learning,
- be an important link between systems designers, programmers, and interaction designers in industry as well as in research projects.
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